Methods and Systems for an Intelligent Technical Debt Helper Bot

1. An intelligent technical debt helper bot system, comprising: an artificial intelligence neural network model trained to identify forms of computer program code that contribute to increases in a level of technical debt; and a computing device comprising one or more processors and one or more memory components communicatively coupled to the one or more processors and the artificial intelligence neural network model, wherein the computing device is configured to: receive a first computer program code; receive a second computer program code comprising one or more changes of the first computer program code; determine, using the artificial intelligence neural network model, whether the one or more changes increase the level of technical debt above a technical debt threshold; and output an indication that the one or more changes exceed the technical debt threshold.

2. The intelligent technical debt helper bot system of claim 1, wherein the indication comprises code contributing to the increase in the level of technical debt above the technical debt threshold.

3. The intelligent technical debt helper bot system of claim 1, wherein output of the indication prevents one or more actions associated with the second computer program code comprising at least one of saving, implementing, committing, or finalizing the one or more changes.

4. The intelligent technical debt helper bot system of claim 1, wherein the one or more changes comprises a re-arrangement of code of the first computer program code, an addition to the first computer program code, removal of code from the first computer program code, or combinations thereof.

5. The intelligent technical debt helper bot system of claim 1, wherein the computing device is further configured to generate, using the artificial intelligence neural network model and based on the second computer program code, an automated code recommendation to address technical debt of the second computer program code in response to the indication that the one or more changes exceed the technical debt threshold, wherein the artificial intelligence neural network model is trained to generate the automated code recommendation learned from one or more sets of computer program code labeled with a corresponding technical debt.

6. The intelligent technical debt helper bot system of claim 5, wherein the computing device is further configured to: implement the automated code recommendation as an implemented automated code recommendation; and update the level of technical debt based on the implemented automated code recommendation.

7. The intelligent technical debt helper bot system of claim 5, wherein the computing device is further configured to implement the automated code recommendation.

8. The intelligent technical debt helper bot system of claim 1, wherein the artificial intelligence neural network model is trained on a set of predetermined coding rules, a set of computer program code having zero technical debt, historical technical debt data, or combinations thereof.

9. The intelligent technical debt helper bot system of claim 1, wherein the computing device is further configured to train the artificial intelligence neural network model using machine learning based on an automated code recommendation, acceptance or rejection of the automated code recommendation, or combinations thereof.

10. The intelligent technical debt helper bot system of claim 1, wherein the computing device is further configured to: determine that the one or more changes to the first computer program code is a user change; determine, using the artificial intelligence neural network model, whether the user change contributes to an increase of the level of technical debt; and prevent a user from implementing the user change when the user change contributes to increasing the level of technical debt.

11. An intelligent technical debt helper bot method, the method comprising: receiving, with a computing device comprising one or more processors and one or more memory components, a first computer program code; receiving, with the computing device, a second computer program code comprising one or more changes of the first computer program code; determining, using an artificial intelligence neural network model, whether the one or more changes increase a level of technical debt above a technical debt threshold, wherein the artificial intelligence neural network model is trained to identify forms of computer program code that contribute to increases in the level of technical debt; and outputting, with the computing device, an indication that the one or more changes exceed the technical debt threshold.

12. The intelligent technical debt helper bot method of claim 11, wherein the indication comprises code contributing to the increase in the level of technical debt above the technical debt threshold.

13. The intelligent technical debt helper bot method of claim 11, wherein outputting the indication prevents one or more actions associated with the second computer program code comprising at least one of saving, implementing, committing, or finalizing the one or more changes.

14. The intelligent technical debt helper bot method of claim 11, wherein the one or more changes comprises a re-arrangement of code of the first computer program code, an addition to the first computer program code, removal of code from the first computer program code, or combinations thereof.

15. The intelligent technical debt helper bot method of claim 11, further comprising generating, using the artificial intelligence neural network model and based on the second computer program code, an automated code recommendation to address technical debt of the second computer program code in response to the indication that the one or more changes exceed the technical debt threshold, wherein the artificial intelligence neural network model is trained to generate the automated code recommendation learned from one or more sets of computer program code labeled with a corresponding technical debt.

16. The intelligent technical debt helper bot method of claim 15, further comprising: implementing the automated code recommendation as an implemented automated code recommendation; and updating the level of technical debt based on the implemented automated code recommendation.

17. The intelligent technical debt helper bot method of claim 15, further comprising implementing the automated code recommendation.

18. The intelligent technical debt helper bot method of claim 11, wherein the artificial intelligence neural network model is trained on a set of predetermined coding rules, a set of computer program code having zero technical debt, historical technical debt data, or combinations thereof.

19. The intelligent technical debt helper bot method of claim 11, further comprising training the artificial intelligence neural network model using machine learning based on an automated code recommendation, acceptance or rejection of the automated code recommendation, or combinations thereof.

20. The intelligent technical debt helper bot method of claim 11, further comprising: determining that the one or more changes to the first computer program code is a user change; determining, using the artificial intelligence neural network model, whether the user change contributes to an increase of the level of technical debt; and preventing a user from implementing the user change when the user change contributes to increasing the level of technical debt.